Building Great Machine Learning Experiences In Gmail

The challenges of designing great user experiences for machine learning.

Machine learning is arguably the most important trend in technology today. From predicting what you’re going to say before you say it to fabricating lifelike videos, ML is a powerful technology.

But designing great user experiences for machine learning -powered features presents unique challenges to a product designer: How do you create a mental model for a system with thousands of parameters? How do you explain recommendations from a system that has no rules? How do you provide user control? How do you respect user privacy expectations and tackle issues like ML fairness?

In this talk, Paul Lambert, Product Manager @ Google discusses the challenges he and his team encountered and techniques they developed in building machine learning features in Gmail and Inbox. He has worked on Smart Compose, Smart Reply, Nudging, Priority Inbox, Highlights and other ML-powered productivity features shipped to over a billion users.